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What a Difference a Day Makes: Spring Snowmelt in the Sierras
D. Peterson, M. Dettinger, D. Cayan, R. Smith, L. Riddle and N. Knowles
The basic evolution of a spring snowmelt cycle in the West seems to start with a change in atmospheric circulation. A low pressure (winter) pattern is replaced (within days) by a strong and expanding high-pressure pattern, accompanied by high air temperature and a persistent surge in snowmelt-driven discharge (Cayan, in this issue). This, at least for purposes of discussion, might be called a hydroclimatic spring transition (Fig. 4), upper panel. This transition may or may not show a relation to the presumably more fickle (?) oceanographic/atmospheric spring transition (c.f., Strub et.al, 1988, for a discussion of the oceanographic spring and fall transition).

Following the typical strong surge in discharge, the temperature response coefficients (bi) in equation (1) largely track the rise in discharge as temperature increases its control over the snowmelt process. At some point the system is saturated (the rise in coefficients tends to flatten out). This phase is followed by a steady decline. This point of the decline, where the sum of the coefficients (or gain) decreases, might be a summer transition (Fig. 4, lower panel we are not aware of an oceanographic counterpart summer transition).

The initial stages of forecasting spring snowmelt discharge using statistical-dynamical time series are encouraging. These methods provide some insight into the response characteristics of the system, but we need to test further the forecasting power in our data-derived coefficients (cf., Dettinger, this issue). We know the coefficients vary from year-to-year and tend to be higher in wet than in dry years. The alternating use of a Kalman filter with the difference equation appears to extend forecasts beyond low risk 1-day forecasts which use only observed discharge values. Also, multi-parameter models such as input of the daily variations in high-elevation snowpack as well as air temperature, may better constrain predictions, but such records are short. As the model complexity increases, it makes more sense to use physically-based models (Jeton and Smith, 1993; Jeton et.al, 1996). In closing, we have only scratched the surface, and, as you can see (Fig. 6), there are many options.

Cartoon of an overjoyed (overwhelmed?) scientist pondering which method to select next in time series analysis of the atmospheric - hydrologic system

Figure 6. Cartoon of an overjoyed (overwhelmed?) scientist pondering which method to select next in time series analysis of the atmospheric - hydrologic system.

References

Brown, R.G. and Hwang, P.Y., 1997, Introduction to Random Signals and Applied Kalman Filtering, 3rd. Ed., John Wiley and Sons, N.Y., 484 pp.

Cayan, D.R., 1996, Interannual climate variability and snowpack in the Western United States, Journal of Climate, 9 (5): 928-948.

Cayan, D.R. and Peterson, D.H., 1993, Spring climate and salinity in the San Francisco Bay estuary. Water Resources Research, 29: 293-303.

Cayan, D.R., Riddle, L.G. and Aguado, E., 1993, The influence of precipitation and temperature on seasonal stream flows in California, Water Resources Research, 29: 1127-1140.

Cayan, D.R. Peterson, D.H., Riddle, L., Dettinger, M.D., and Smith, R.E., in this issue, the spring runoff pulse from the Sierra Nevada, 14 pp.

Clow, D.W., Mast, M.A. and Campbell, D.H., 1996, Controls on surface water chemistry in the upper Merced River basin, Yosemite National Park, California, Hydrological Processes 10:727-746.

Cobb and Biesecker, 1971, The National Hydrologie Benchmark Network, USGS Circular 460-D 38 pp.

Dettinger M., Peterson, D., Diaz, H. and Cayan D., in this issue, Forecasting Spring runoff pulses from the Sierra Nevada, 6 pp.

Dettinger, M.D. and Cayan, D.R., 1995, Large-scale atmospheric forcing of recent trends toward early snowmelt runoff in California, Journal of Climate, 8: 606-623.

Jeton, A.E. and Smith, J.L., 1993, Development of watershed models for two Sierra Nevada basins using a geographic information system, Water Resource Bulletin, 29: 923-932.

Jeton, A.E., Dettinger, M.D., and Smith, J.L., 1996, Potential effects of climate change on streamflow, eastern and western slopes of the Sierra Nevada, California and Nevada: U.S. Geological Survey Water Resources Investigations Report 95-4260, 44 p.

Lawrence, C.L., 1987, Streamflow characteristics at hydrologic benchmark stations, USGS Circular 941, 123 pp.

Ljung, L., 1995, System Identification Toolbox, The Math Works, Inc., Natick, Mass.

Ljung, L., 1987, System Identification-Theory for the Users, Prentice Hall, Englewood Cliffs, N.J.

Morris, E.M., 1985, Snow and ice, in M.G. Anderson and T.P. Burt Eds., Hydrological Forecasting, John Wiley and Sons Ltd., New York, pp. 153-182.

Strub, P.T. and James, C., 1988, Atmospheric conditions during the spring and fall transitions in the coastal ocean off western United States, Journal of Geophysical Research, v. 93, no. C12, 15561: 15584.

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